Alois Ferscha, Dominik Moser, Andreas Riener, Kashif Zia,
"Deliverable D2.3: Report on Concepts for Dealing with Uncertain Data and the Integration of Real World Data into the Simulation"
, Institut für Pervasive Computing, Altenberger Strasse 69, 4040 Linz, 1-2011
Deliverable D2.3: Report on Concepts for Dealing with Uncertain Data and the Integration of Real World Data into the Simulation
Sprache des Titels:
One more and more important issue to cope with in the analysis of large systems with heavy interaction load amongst its parts (i. e., subsystems) is to deal with unreliable and noisy data caused by unreliable, error prone, faulty, etc. sensing technology. This involves, aside the well known statistical approaches for error and/or noise reduction in data sets, the development of new means and data aggregation techniques to allow for both qualitative and quantitative compensation of missing, corrupted, unreliable, noisy, and manipulated data. In particular, the questions to be addressed within this deliverable are: 1. How can noisy (or dirty) data be defined?, 2. What are general data representation techniques suitable for noisy data, 3. How to query data from complex and dynamic environments?, 4. What are statistical approaches for dealing with noisy data? data cleaning, 5. What kind of sensor faults may appear (to SOCIONICAL data)?, 6. What are methods/techniques for detecting/correcting sensor faults, 7. Which approach is suitable for what problem (in the domain of SOCIONICAL)?, 8. How to avoid data manipulation; if happened, how to detect manipulated data?, and 9. To what extent should one trust information provided by AmI technology (technical systems)?